LIDAR-based model reconstruction for spacecraft pose determination

This paper deals with the problem of 3D surface reconstruction processing point clouds produced by a LIDAR. In the framework of an algorithmic architecture for pose determination of an uncooperative spacecraft, this functionality is required to update the existing model of the target geometry (reference model), if a non-negligible inconsistency with respect to its real geometry is detected. Hence, two original approaches to generate triangular mesh models from point clouds are developed, which are based on the marching-cube and Delaunay triangulation concepts, respectively. The output of these techniques can then be exploited within an original algorithmic strategy conceived to carry out the update function on the reference model, aiming at improving pose estimation accuracy. The two 3D surface reconstruction approaches are tested over point clouds acquired using a new prototype of the RVS 3000-3D
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LIDAR produced by Jena-Optronik GmbH and a satellite mock-up as target. Their compatibility for real-time implementation on FPGA hardware is also preliminary evaluated. Finally, performance assessment of the proposed strategy for on-line update of the reference model is carried out within an ad-hoc experimental setup, using a Kinect V2 sensor to acquire point clouds of a scaled satellite mock-up.